Based on the real-time, on-line PM2.5 monitoring data from 206 monitoring stations in Tangshan City, during three different periods, including heating period, heavy pollution period, and non-heating period, respectively, this research was to study the spatial distribution characteristics and spatial autocorrelation of air pollution so as to provide the basis to enhance air pollution control in Tangshan City, by using ArcGIS as the platform. All three periods had a certain spatial autocorrelation and the global spatial autocorrelation during heavy pollution period was the strongest. During heating and heavy pollution periods, the High-High cluster of PM2.5 mainly occurred in the central areas of Tangshan, while the Low-Low cluster was mainly distributed in the northern mountain areas and a small portion in coastal areas. High-High cluster of non-heating period was mainly distributed in Fengrun District and Fengnan District, while Low-Low cluster occurred in the northern part of Zunhua. Through spatial interpolation, the PM2.5 distribution of the whole city was simulated to result that the highest grid point value of PM2.5 in Tangshan is 241μg/m3 during heavy pollution period, while the lowest value is only 37μg/m3 in non-heating period. Based on the characteristics of PM2.5 concentration variation and spatial distribution, the 18 districts and counties of Tangshan were divided into 5 zones, and corresponding suggestions on PM2.5 control measures for each zone were proposed.
刘靖, 单春艳, 梁晓宇. 唐山市基于GIS的PM2.5空间聚集性及分区管控[J]. 中国环境科学, 2020, 40(2): 513-522.
LIU Jing, SHAN Chun-yan, LIANG Xiao-yu. Research on spatial aggregation of PM2.5 and zoning control in Tangshan based on GIS. CHINA ENVIRONMENTAL SCIENCECE, 2020, 40(2): 513-522.
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